Journal of Intelligent & Robotic Systems

, Volume 68, Issue 2, pp 165–184

A Novel Trajectory Generation Method for Robot Control

Authors

    • Bernstein Center for Computational Neuroscience, Inst. of Physics IIIUniversity of Göttingen
    • Research & Technology, Lenovo
  • Tomas Kulvicius
    • Bernstein Center for Computational Neuroscience, Inst. of Physics IIIUniversity of Göttingen
  • Minija Tamosiunaite
    • Bernstein Center for Computational Neuroscience, Inst. of Physics IIIUniversity of Göttingen
  • Florentin Wörgötter
    • Bernstein Center for Computational Neuroscience, Inst. of Physics IIIUniversity of Göttingen
Open AccessArticle

DOI: 10.1007/s10846-012-9683-8

Cite this article as:
Ning, K., Kulvicius, T., Tamosiunaite, M. et al. J Intell Robot Syst (2012) 68: 165. doi:10.1007/s10846-012-9683-8

Abstract

This paper presents a novel trajectory generator based on Dynamic Movement Primitives (DMP). The key ideas from the original DMP formalism are extracted, reformulated and extended from a control theoretical viewpoint. This method can generate smooth trajectories, satisfy position- and velocity boundary conditions at start- and endpoint with high precision, and follow accurately geometrical paths as desired. Paths can be complex and processed as a whole, and smooth transitions can be generated automatically. Performance is analyzed for several cases and a comparison with a spline-based trajectory generation method is provided. Results are comparable and, thus, this novel trajectory generating technology appears to be a viable alternative to the existing solutions not only for service robotics but possibly also in industry.

Keywords

Trajectory generation Dynamic trajectory joining Control theory Machine learning

Copyright information

© The Author(s) 2012